Browsing by Author Gu, Quanquan

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TitleAuthor(s)Issue DateViews
 
Benign Overfitting in Two-layer Convolutional Neural Networks
Proceeding/Conference:NeurIPS 2022 (28/11/2022-09/12/2022, New Orleans )
Cao, YuanChen, ZixiangBelkin, MikhailGu, Quanquan
9-Dec-2022
 
Closing the generalization gap of adaptive gradient methods in training deep neural networks
Proceeding/Conference:Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence
Chen, JinghuiZhou, DongruoTang, YiqiYang, ZiyanCao, YuanGu, Quanquan
2020
10
 
Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States
Journal:Proceedings of the National Academy of Sciences of the United States of America
Cramer, Estee Y.Ray, Evan L.Lopez, Velma K.Bracher, JohannesBrennen, AndreaCastro Rivadeneira, Alvaro J.Gerding, AaronGneiting, TilmannHouse, Katie H.Huang, YuxinJayawardena, DasuniTurtle, James A.Ben-Nun, MichalRiley, StevenRiley, PeteKoyluoglu, UgurDesRoches, DavidForli, PedroHamory, BruceKyriakides, ChristinaLeis, HelenKanji, Abdul H.Milliken, JohnMoloney, MichaelMorgan, JamesNirgudkar, NinadOzcan, GokcePiwonka, NoahRavi, MattSchrader, ChrisShakhnovich, ElizabethSiegel, DanielKhandelwal, AyushSpatz, RyanStiefeling, ChrisWilkinson, BarrieWong, AlexanderCavany, SeanEspaña, GuidoMoore, SeanOidtman, RachelPerkins, AlexKraus, DavidLe, KhoaKraus, AndreaGao, ZhifengBian, JiangCao, WeiLavista Ferres, JuanLi, ChaozhuoLiu, Tie YanXie, XingZhang, ShunZheng, ShunMühlemann, AnjaVespignani, AlessandroChinazzi, MatteoDavis, Jessica T.Mu, KunpengPastore Y Piontti, AnaXiong, XinyueZheng, AndrewBaek, JackieFarias, VivekGeorgescu, AndreeaNiemi, JaradLevi, RetsefSinha, DeekshaWilde, JoshuaPerakis, GeorgiaBennouna, Mohammed AmineNze-Ndong, DavidSinghvi, DivyaSpantidakis, IoannisThayaparan, LeannTsiourvas, AsteriosShah, ApurvSarker, ArnabJadbabaie, AliShah, DevavratDella Penna, NicolasCeli, Leo A.Sundar, SakethWolfinger, RussOsthus, DaveCastro, LaurenFairchild, GeoffreyStark, ArianeMichaud, IsaacKarlen, DeanKinsey, MattMullany, Luke C.Rainwater-Lovett, KaitlinShin, LaurenTallaksen, KatharineWilson, ShelbyLee, Elizabeth C.Dent, JuanWang, YijinGrantz, Kyra H.Hill, Alison L.Kaminsky, JoshuaKaminsky, KathrynKeegan, Lindsay T.Lauer, Stephen A.Lemaitre, Joseph C.Lessler, JustinMeredith, Hannah R.Perez-Saez, JavierWattanachit, NutchaShah, SamSmith, Claire P.Truelove, Shaun A.Wills, JoshMarshall, MaximilianGardner, LaurenNixon, KristenBurant, John C.Wang, LilyGao, LeiZorn, Martha W.Gu, ZhilingKim, MyungjinLi, XinyiWang, GuannanWang, YueyingYu, ShanReiner, Robert C.Barber, RyanGakidou, EmmanuelaHay, Simon I.Gu, YouyangLim, SteveMurray, ChrisPigott, DavidGurung, Heidi L.Baccam, PrasithStage, Steven A.Suchoski, Bradley T.Prakash, B. AdityaAdhikari, BijayaCui, JiamingJain, SansiddhRodríguez, AlexanderTabassum, AnikaXie, JiajiaKeskinocak, PinarAsplund, JohnBaxter, ArdenOruc, Buse EylulSerban, NicoletaArik, Sercan O.Dusenberry, MikeBannur, NayanaEpshteyn, ArkadyKanal, ElliLe, Long T.Li, Chun LiangPfister, TomasSava, DarioSinha, RajarishiTsai, ThomasYoder, NateYoon, JinsungDeva, AyushZhang, LeyouAbbott, SamBosse, Nikos I.Funk, SebastianHellewell, JoelMeakin, Sophie R.Sherratt, KatharineZhou, MingyuanKalantari, RahiYamana, Teresa K.Kulkarni, MihirPei, SenShaman, JeffreyLi, Michael L.Bertsimas, DimitrisSkali Lami, OmarSoni, SakshamTazi Bouardi, HamzaAyer, TurgayAdee, MadelineChhatwal, JagpreetMerugu, SrujanaDalgic, Ozden O.Ladd, Mary A.Linas, Benjamin P.Mueller, PeterXiao, JadeWang, YuanjiaWang, QinxiaXie, ShanghongZeng, DonglinGreen, AldenRaval, AlpanBien, JacobBrooks, LoganHu, Addison J.Jahja, MariaMcDonald, DanielNarasimhan, BalasubramanianPolitsch, CollinRajanala, SamyakRumack, AaronSimon, NoahShingi, SiddhantTibshirani, Ryan J.Tibshirani, RobVentura, ValerieWasserman, LarryO'Dea, Eamon B.Drake, John M.Pagano, RobertTran, Quoc T.Ho, Lam Si TungHuynh, HuongTiwari, AvtanshWalker, Jo W.Slayton, Rachel B.Johansson, Michael A.Biggerstaff, MatthewReich, Nicholas G.White, JeromeAbernethy, Neil F.Woody, SpencerDahan, MaytalFox, SpencerGaither, KellyLachmann, MichaelMeyers, Lauren AncelScott, James G.Tec, MauricioSrivastava, AjiteshGeorge, Glover E.Cegan, Jeffrey C.Dettwiller, Ian D.England, William P.Farthing, Matthew W.Hunter, Robert H.Lafferty, BrandonLinkov, IgorMayo, Michael L.Parno, Matthew D.Rowland, Michael A.Trump, Benjamin D.Zhang-James, YanliChen, SamuelFaraone, Stephen V.Hess, JonathanMorley, Christopher P.Salekin, AsifWang, DongliangCorsetti, Sabrina M.Baer, Thomas M.Eisenberg, Marisa C.Falb, KarlHuang, YitaoMartin, Emily T.McCauley, EllaMyers, Robert L.Schwarz, TomSheldon, DanielGibson, Graham CaseyYu, RoseGao, LiyaoMa, YianWu, DongxiaYan, XifengJin, XiaoyongWang, Yu XiangChen, Yang QuanGuo, LihongZhao, YantingGu, QuanquanChen, JinghuiWang, LingxiaoXu, PanZhang, WeitongZou, DifanBiegel, HannahLega, JocelineMcConnell, SteveNagraj, V. P.Guertin, Stephanie L.Hulme-Lowe, ChristopherTurner, Stephen D.Shi, YunfengBan, XuegangWalraven, RobertHong, Qi JunKong, Stanleyvan de Walle, Axel
2022
3
 
Faster Convergence of Stochastic Gradient Langevin Dynamics for Non-Log-Concave Sampling
Proceeding/Conference:37th Conference on Uncertainty in Artificial Intelligence, UAI 2021
Zou, DifanXu, PanGu, Quanquan
2021
6
 
Generalization bounds of stochastic gradient descent for wide and deep neural networks
Proceeding/Conference:Advances in Neural Information Processing Systems 32 (NeurIPS 2019)
Cao, YuanGu, Quanquan
2019
12
 
Generalization error bounds of gradient descent for learning over-parameterized deep relu networks
Proceeding/Conference:Proceedings of the AAAI Conference on Artificial Intelligence
Cao, YuanGu, Quanquan
2020
13
 
Global convergence of Langevin dynamics based algorithms for nonconvex optimization
Proceeding/Conference:Advances in Neural Information Processing Systems
Xu, PanZou, DifanChen, JinghuiGu, Quanquan
2018
2
 
Gradient descent optimizes over-parameterized deep ReLU networks
Journal:Machine Learning
Zou, DifanCao, YuanZhou, DongruoGu, Quanquan
2020
20
 
Laplacian smoothing stochastic gradient markov chain monte carlo
Journal:SIAM Journal on Scientific Computing
WANG, BAOZOU, DIFANGU, QUANQUANOSHER, STANLEY J.
2021
 
Layer-dependent importance sampling for training deep and large graph convolutional networks
Proceeding/Conference:Advances in Neural Information Processing Systems
Zou, DifanHu, ZiniuWang, YewenJiang, SongSun, YizhouGu, Quanquan
2019
2
 
Learning High-Dimensional Single-Neuron ReLU Networks with Finite Samples
Proceeding/Conference:International Conference on Machine Learning (17/07/2022-23/07/2022, Baltimore)
Wu, JingfengZou, DifanChen, ZixiangBraverman, VladimirGu, QuanquanKakade, Sham M
23-Jul-2022
 
Risk Bounds of Multi-Pass SGD for Least Squares in the Interpolation Regime
Proceeding/Conference:Advances in Neural Information Processing Systems (28/11/2022-09/12/2022, New Orleans)
Zou, DifanWu, JingfengBraverman, VladimirGu, QuanquanKakade, Sham M
12-Dec-2022
 
Sampling from non-log-concave distributions via stochastic variance-reduced gradient Langevin dynamics
Proceeding/Conference:AISTATS 2019 - 22nd International Conference on Artificial Intelligence and Statistics
Zou, DifanXu, PanGu, Quanquan
2020
2
 
Stochastic gradient hamiltonian monte carlo methods with recursive variance reduction
Proceeding/Conference:Advances in Neural Information Processing Systems
Zou, DifanXu, PanGu, Quanquan
2019
1
 
Stochastic variance-reduced Hamilton Monte Carlo methods
Proceeding/Conference:35th International Conference on Machine Learning, ICML 2018
Zou, DifanXu, PanGu, Quanquan
2018
3
 
Subsampled stochastic variance-reduced gradient langevin dynamics
Proceeding/Conference:34th Conference on Uncertainty in Artificial Intelligence 2018, UAI 2018
Zou, DifanXu, PanGu, Quanquan
2018
5
 
The Benefits of Implicit Regularization from SGD in Least Squares Problems
Proceeding/Conference:Advances in Neural Information Processing Systems
Zou, DifanWu, JingfengBraverman, VladimirGu, QuanquanFoster, Dean P.Kakade, Sham M.
2021
12
 
The Benefits of Mixup for Feature Learning
Proceeding/Conference:Fortieth International Conference on Machine Learning (ICML) (23/07/2023-29/07/2023, Honolulu, Hawaii, USA)
Zou, DifanCao, YuanLi, YuanzhiGu, Quanquan
23-Jul-2023
 
The Implicit Bias of Batch Normalization in Linear Models and Two-layer Linear Convolutional Neural Networks
Proceeding/Conference:36th Annual Conference on Learning Theory (COLT 2023) (12/07/2023-15/07/2023, Bangalore, India)
Cao, YuanZou, DifanLi, YuanzhiGu, Quanquan
15-Jul-2023
 
The Power and Limitation of Pretraining-Finetuning for Linear Regression under Covariate Shift
Proceeding/Conference:Advances in Neural Information Processing Systems (28/11/2022-09/12/2022, New Orleans)
Wu, JingfengZou, DifanBraverman, VladimirGu, QuanquanKakade, and Sham M
12-Dec-2022
Showing results 5 to 24 of 28 < previous   next >